Clusters composed of the following variables: Overall mortality from diabetes mellitus adjusted for age for the period from 2010 to 2019, Overall mortality from circulatory system diseases adjusted for age for the period from 2010 to 2019, Overall mortality from chronic respiratory diseases adjusted for age for the period from 2010 to 2019, Overall mortality from malignant neoplasms adjusted for age for the period from 2010 to 2019, hospital morbidity in the SUS (Unified Health System) from diabetes mellitus adjusted for age for the period from 2010 to 2019, Hospital morbidity in the SUS from circulatory system diseases adjusted for age for the period from 2010 to 2019, Hospital morbidity in the SUS from chronic respiratory diseases adjusted for age for the period from 2010 to 2019, Hospital morbidity in the SUS from malignant neoplasms adjusted for age for the period from 2010 to 2019. .
* The mortality rates are based on 100,000 inhabitants.
* The hospital morbidity rates are based on 10,000 SUS-dependented inhabitants.
* All rates were normalized using z-score for the creation of clusters.
* The SKATER algorithm was used for clustering, as the goal is to create contiguous regions with similar morbidity and mortality profiles.
* The queen method of order 1 was adopted as the neighborhood criterion. The city of Ilhabela, which has no direct neighbors, was assigned to the nearest cluster.